Subgroup Discovery for Weight Learning in Breast Cancer Diagnosis

Authors:
Beatriz López;Víctor Barrera;Joaquim Meléndez;Carles Pous;Joan Brunet;Judith Sanz
Affiliations:
Institut d'Informática i Aplicacions, Universitat de Girona, Girona, Spain;Institut d'Informática i Aplicacions, Universitat de Girona, Girona, Spain;Institut d'Informática i Aplicacions, Universitat de Girona, Girona, Spain;Institut d'Informática i Aplicacions, Universitat de Girona, Girona, Spain;Institut d'Investigació Biomèdica de Girona and Institut Català d'Oncologia, Girona, Spain;Hospital Sant Pau, Barcelona, Spain
Venue:
AIME '09 Proceedings of the 12th Conference on Artificial Intelligence in Medicine: Artificial Intelligence in Medicine
Year:
2009

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Abstract

In the recent years, there is an increasing interest of the use of case-based reasoning (CBR) in medicine. CBR is an approach to problem solving that is able to use specific knowledge of previous experiences. However, the efficiency of CBR strongly depends on the similarity metrics used to recover past experiences. In such metrics, the role of attribute weights is critical. In this paper we propose a methodology that use subgroup discovery methods to learn the relevance of the attributes. The methodology is applied to a Breast Cancer dataset obtaining significant improvements. ...